Abstract

Intuitive statistical inferential judgments involve the estimation of statisticalproperties of samples of information, such as the mean or variance. Prior researchhas shown that human judges are generally good at making unbiased estimates ofsample properties. However, a series of recent applied consumer researchexperiments demonstrated a systematic bias in comparative judgments of itemdistributions in which the individual items are paired across those distributions, forexample comparing the prices in two stores selling the same items. When the twodistributions have the same mean, the distribution with the higher number of itemsthat are smaller in magnitude than the equivalent item in the other distribution istypically judged to be the smaller of the two distributions: a frequency bias. In aseries of experiments, the research in this thesis provides a robust demonstration ofthe frequency bias and explores possible explanations for the bias. A comparisonbetween simultaneous and sequential presentation of information demonstrates thatthe frequency bias cannot solely be explained by the salience of the frequency cue.A novel web-based experiment, in which information was sampled incidentally fromthe environment and a naturalistic task was used to elicit comparative judgments,showed that the frequency effect persists in an ecologically-valid context. Asystematic comparison between alternative cognitive models of the judgment processsupports an explanation in which items are recalled from memory and compared in apair-wise fashion, meaning the frequency bias may be found in a wide range of otherjudgment tasks and domains, which would have significant implications for ourunderstanding of intuitive comparative judgments.